Latent Class Growth Mixture Modeling Research Articles

Abstract 4121890: Resting Heart Rate Trajectories over 25 Years: Patterns, Predictors, and Prognostic Impact in the Atherosclerosis Risk in Communities (ARIC) Study

Background: Abnormal resting heart rate (RHR) is associated with cardiovascular events and mortality. Longitudinal RHR trajectories may offer unique prognostic, but research exploring these trajectories over extended periods and their prognostic implications is limited. Methods: Using data from 5,794 participants in the Atherosclerosis Risk in Communities (ARIC) study, we first characterized RHR trajectories over 25 years (from visit 1 [1987-89] to visit 5 [2011-13]) with latent class growth mixture models. Then, we determined the predictors of those trajectories using multinomial logistic regression (n=5,432 with data on predictors of interest). We ran Cox models to quantify the associations between RHR trajectories with cardiovascular outcomes (coronary heart disease, heart failure, stroke) and all-cause mortality (n=4,329 free of cardiovascular disease at baseline). Results: We identified one typical pattern (stable/slight decline, 88.4%) and three atypical patterns (stable-slight increase, 9.2%; increase-decrease, 2.0%; stable-sharp increase, 0.4%) (Figure-Left panel). Obesity, ever smoking, a history of heart failure, and lower education levels predicted the atypical patterns. The stable-increase (combined for slight and sharp) trajectory was significantly and robustly associated with heart failure and all-cause mortality (Figure-Right panel). The increase-decrease trajectory showed a hazard ratio of ~2 for coronary heart disease, although statistical significance was restricted in the demographically adjusted model. Conclusions: We identified one typical (stable/slight decline) and three atypical (increase-decrease, stable-slight increase, and stable-sharp increase) RHR trajectories over 25 years. The atypical trajectories, particularly the stable-increase pattern, were associated with poorer prognosis. These findings highlight the value of monitoring long-term RHR trajectories for cardiovascular risk assessment.

The association of multi-system conditions on mental health trajectories during naval deployment

ABSTRACT This study seeks to enhance understanding of mental health trajectories across Navy deployments and the predictors of those trajectories by exploring a range of job design and individual-level factors. Personnel from the Royal Australian Navy were surveyed on pre-deployment, mid-deployment, and post-deployment. At pre-deployment, there were 559 (M age = 30.19; male = 75.5%) survey responses, N = 112 survey responses could be linked at all time points (retention rate of 20.04% across all time points), and 314 personnel (56.2%) responded at least twice. Latent class growth analyses and growth mixture models were used to determine the trajectories that best fit the data. Separate models were developed for each of the mental health outcomes studied (i.e. psychological distress, perceived resilience, and perceived stress), plus a latent outcome representing a summary measure of psychological ill-health. This latent outcome, estimated as the most comprehensive assessment approach, was used to evaluate all 33 predictors. Consistent with previous work, we identified between two and four trajectories reflecting resilient/low symptom trajectories and heterogeneous symptom trajectories. There were a greater proportion of personnel in the heterogeneous symptom trajectories than identified in previous research. A key contribution of this work is the thorough comparison and ranking of factors that influence the deployment experience. We emphasize the importance of role demands and resources in determining these trajectories when compared directly to self-regulation strategies. Study findings highlight important implications for job design for military personnel during deployment and underscore the importance of adopting a holistic system approach to well-being.

Characterizing within-person variance in, and menstrual cycle associations with, event-related potentials associated with positive and negative valence systems: The reward positivity and the error-related negativity

Event-related potentials (ERPs) are widely employed as measures of transdiagnostic cognitive processes that are thought to underlie various clinical disorders (Hajcak et al., 2019). Despite their prevalent use as individual difference measures, the effects of within-person processes, such as the human menstrual cycle, on a broad range of ERPs are poorly understood. The present study leveraged a within-subject design to characterize between- and within-person variance in ERPs as well as effects of the menstrual cycle in two frequently studied ERPs associated with positive and negative valence systems underlying psychopathology—the Reward Positivity (RewP) and the Error- Related Negativity (ERN). Seventy-one naturally-cycling participants completed repeated EEG and ecological momentary assessments of positive and negative affect in the menstrual cycle's early follicular, periovulatory, and mid-luteal phases. We examined the mean degree of change between cycle phases in both ERPs, the between-person variability in the degree of change in both ERPs, and whether an individual’s degree of cyclical change in these ERPs show coherence with their degree of cyclical change in positive and negative affect recorded across the cycle. Results revealed no significant changes in positive and negative affect across the cycle and rather small changes in ERP amplitudes. Significant random slopes in our model revealed larger individual differences in trajectories of change in ERP amplitudes and affect, in agreement with prior evidence of heterogeneity in dimensional hormone sensitivity. Additionally, state-variance in these ERPs correlated with positive and negative affect changes across the cycle, suggesting that cycle-mediated ERP changes may have relevance for affect and behavior. Finally, exploratory latent class growth mixture modeling revealed subgroups of individuals that display disparate patterns of change in ERPs that should be further investigated.

Impact of adiposity indices changes across the lifespan on risk of diabetes in women: trajectory modeling approach

AimsThe impact of life-course different adiposity indices on diabetes mellitus (DM) is poorly understood. We aimed to do trajectory analysis with repeated measurements of adiposity indices in the development of DM among women across the lifespan.MethodsThis study prospectively investigated the 1,681 population of Tehran Lipid and Glucose Study. At baseline, all individuals were free of diabetes. Trajectory analysis was used to identify homogeneous distinct clusters of adiposity indices trajectories and assign individuals to unique clusters.ResultsOf the 1681 healthy women, 320 progressed to the DM. Three distinct body mass index (BMI) trajectories and 2 distinct trajectories of other adiposity indices (waist circumstance (WC), conicity index (C-index), and body roundness index (BRI)) were chosen as the best fitting of the latent class growth mixture model. In the adjusted model, total participants [HR (CI 95%): 2.83 (2.05, 3.91); p < 0.001], and menopause [1.35 (1.10, 2.11); p = 0.001] and reproductive-age women [2.93 (1.80, 4.78); p = 0.003] of the high BMI trajectory compared to the ones in the low trajectory of BMI were more likely to develop DM. The high BRI in menopause had a significantly higher risk of DM compared to the low trajectory. In menopause (1.80 (1.26, 2.58)) and reproductive-age women (4.32 (2.49, 7.47)) with high trajectory of C-index, the DM risk decreased after adjustment.ConclusionsThe risk of DM was greater for high BMI, WC, C-index, and BRI trajectories than for lower trajectories. Hence, the development of general, abdominal, and visceral obesity trajectories in the prevention of DM should be considered by clinicians.

Using machine learning to explore the predictors of life satisfaction trajectories in older adults.

Life satisfaction is vital for older adults' well-being, impacting various life aspects. It is dynamic, necessitating nuanced approaches to capture its trajectories accurately. This study aimed to explore the diverse trajectories and predictors of life satisfaction among older adults in China using longitudinal data from the China Health and Retirement Longitudinal Study. Latent class growth modeling and growth mixture modeling were employed to identify distinct trajectories of life satisfaction. Machine learning (ML) models were developed to predict different trajectories and identify important predictors of different trajectories. Four distinct trajectories of life satisfaction were identified, showcasing nuanced patterns of life satisfaction that changed over time. ML models, especially random forest, effectively predicted these trajectories. Emotional experiences (particularly the frequency of happiness and loneliness), body mass index, and self-report health emerged as significant predictors of different life satisfaction trajectories. Our finding revealed the importance of focusing on individuals or groups with consistently low life satisfaction and paying more attention to mental and physical health predictors. Our models might guide future targeted preventative treatments.

Association of physical activity trajectories over 8 years and risk of knee replacement: data from the osteoarthritis initiative

BackgroundTo identify physical activity (PA) trajectories in adults with or at risk of knee osteoarthritis and to evaluate the association of PA trajectories with incident knee replacement (KR).MethodsThis study used data from the Osteoarthritis Initiative. The Physical Activity Scale for the Elderly and the KR were assessed annually from baseline to 9 years. Individuals were included if they did not undergo KR surgery at baseline and had data on PA at ≥ 1 visit before KR. Latent class growth mixture Modeling was used to identify the optimal trajectories of PA before KR. Log-binomial regression models were used to assess the association between PA trajectories and the risk of KR. Data analyses were conducted in all individuals and those with radiographic osteoarthritis (ROA) and significant knee pain (Western Ontario and McMaster Osteoarthritis Index pain score of ≥ 5 on a 0–20 scale) at baseline, respectively.ResultsOf 4731 participants (mean age 61.1 years, 58.5% female), four distinct and slightly declined PA trajectories were identified. Compared to individuals with a “Low” PA trajectory, those with “Medium-low”, “Medium-high”, or “High” PA trajectories were not significantly associated with the risk of KR (risk ratios: 0.97–1.19, all p > 0.05). Similar PA trajectories and associations with the risk of KR were observed in the subgroups of individuals with radiographic osteoarthritis and those with significant knee pain at baseline, respectively.ConclusionIn participants with or at risk of knee osteoarthritis, PA slightly declines over time and may play no role in the risk of KR.

Associations of longitudinal BMI percentile classification patterns in early childhood with neighborhood-level social determinants of health.

Understanding social determinants of health (SDOH) that may be risk factors for childhood obesity is important to developing targeted interventions to prevent obesity. Prior studies have examined these risk factors, mostly examining obesity as a static outcome variable. We extracted EHR data from 2012-2019 for a children's health system that includes 2 hospitals and wide network of outpatient clinics spanning 5 East Coast states in the US. Using data-driven and algorithmic clustering, we have identified distinct BMI-percentile classification groups in children from 0 to 7 years of age. We used two separate algorithmic clustering methods to confirm the robustness of the identified clusters. We used multinomial logistic regression to examine the associations between clusters and 27 neighborhood SDOHs and compared positive and negative SDOH characteristics separately. From the cohort of 36,910 children, five BMI-percentile classification groups emerged: always having obesity (n=429; 1.16%), overweight most of the time (n=15,006; 40.65%), increasing BMI-percentile (n=9,060; 24.54%), decreasing BMI-percentile (n=5,058; 13.70%), and always normal weight (n=7,357; 19.89%). Compared to children in the decreasing BMI-percentile and always normal weight groups, children in the other three groups were more likely to live in neighborhoods with higher poverty, unemployment, crowded households, single-parent households, and lower preschool enrollment. Neighborhood-level SDOH factors have significant associations with children's BMI-percentile classification and changes in classification. This highlights the need to develop tailored obesity interventions for different groups to address the barriers faced by communities that can impact the weight and health of children living within them. This study demonstrates the association between longitudinal BMI-percentile patterns and SDOH in early childhood. Five distinct clusters with different BMI-percentile trajectories are found and a strong association between these clusters and SDOH is observed. Our findings highlight the importance of targeted prevention and treatment interventions based on children's SDOH.

Association of longitudinal trajectories of fasting plasma glucose with all-cause and cardiovascular mortality among a Chinese older population: a retrospective cohort study

The association between fasting plasma glucose (FPG), an important indicator of overall glycemic status, and the risk of cardiovascular mortality has been well investigated. The longitudinal study can repeatedly collect measured results for the variables to be studied and then consider the potential effects of intraindividual changes in measurement. This study aimed to identify long-term FPG trajectories and investigate the association between trajectory groups and cardiovascular and all-cause mortality. A latent class growth mixture modeling (LCGMM) was used to identify FPG trajectories. Cox proportional hazard models were used to estimate associations between FPG trajectories and the risk of all-cause and cardiovascular mortality. A U-shaped relationship between FPG and all-cause and cardiovascular mortality was observed in the restricted cubic spline regression models. Two FPG longitudinal trajectories of low-level (mean FPG = 5.12mmol/L) and high-level (mean FPG = 6.74mmol/L) were identified by LCGMM. After being adjusted for potential confounders, compared with the low-level category, the hazard ratios (HRs) for all-cause and cardiovascular mortality were 1.23(1.16–1.30) and 1.25(1.16–1.35), respectively, for the high-level group. Long-term FPG trajectories are significantly associated with and potentially impact the risk of all-cause and cardiovascular mortality.

CARDIOVASCULAR RISK FACTOR TRAJECTORIES AND INCIDENT CARDIOVASCULAR DISEASE IN OLDER ADULTS: THE KAILUAN STUDY

Objective: Long-term condition and longitudinal accumulation of cardiovascular risk factor (CRF) may be associated with adverse outcomes in the elderly, but the previous evidence is scarce. We studied the associations of CRF trajectories, their accumulation, with incident cardiovascular disease (CVD) in older adults. Design and method: From 2006, a population-based cohort of 8505 older adults have been repeatedly followed up for 14 years (until 31 December 2020). Blood pressure, serum lipids, height and weight, and blood glucose were assessed in all follow-ups and their trajectories from 2006 to 2010 were identified using latent class growth mixture modeling. Main outcome was incident CVD, which was a composite of coronary revascularization, myocardial infarction, heart failure, or stroke. The associations of CRF trajectories and incident CVD were studied for individual CRF trajectory and their accumulation, using Cox proportional hazards regression models. Results: We identified 3, 4, 2, 2 trajectories for systolic blood pressure (SBP), body mass index (BMI), total cholesterol (TC), and fasting blood glucose (FBG), respectively. Compared with low-increasing SBP, the multivariable-adjusted hazard ratio (HR) and 95% CI were 1.35 (1.19-1.54) for moderate-increasing SBP and 1.54 (1.28-1.86) for high-increasing SBP. Compared with low-stable BMI, the HRs (95% CIs) were 1.30 (1.11-1.53), 1.41 (1.19-1.66), 1.35 (1.07-1.71) for moderate-stable, elevated-stable, and high-stable BMI, respectively. Compared with low-stable TC, the HR (95% CI) were 1.19 (1.06-1.33) for high-stable TC. Compared with low-stable FBG, the HR (95% CI) were 1.38 (1.17-1.63) for high-stable FBG. A positive association was observed for the CRF trajectory accumulation with incident CVD (P for trend &lt; 0.001), with HRs (95% CIs) of 1.54 (1.16-2.04), 2.15 (1.63-2.83), 2.58 (1.93-3.45) and 2.92 (1.95-4.36) for 1, 2, 3, 4 high CRF trajectories, respectively. Sensitivity analyses showed consistent results after excluding those who ever used antihypertensive, antidiabetic, or lipid-lowering drugs during 2006 to 2010, excluding events within the first year of follow-up, and considering death as competing risk. Conclusions: Longitudinal higher CRF trajectory was independently associated with higher CVD risk in older adults. Besides, the higher the number of adverse CRF trajectories, the higher was the observed CVD risk.

P062 Trust performance in managing inflammatory arthritis over time in England and Wales: a latent class analysis approach

Abstract Background/Aims To evaluate trust-level performance in time to initiation of disease-modifying antirheumatic drug (DMARD) therapy in patients with early inflammatory arthritis (EIA), with identification of change in performance trajectories over time and investigation of trust characteristics associated with this change. Methods We included 130 trusts from the UK contributing to the National Early Inflammatory Arthritis Audit (NEIAA) from 2018 to 2020. The primary outcome was days from referral to initiation of DMARD therapy in patients with EIA. Latent class growth mixture models were applied to identify distinct groups of trusts with similar trajectories of performance change over time. We used mixed-effects linear and multinomial logistic regression models to evaluate the association between delay in treatment and trust-level characteristics. Results The mean (SD) time to DMARD initiation was 53 (18) days, with an average 0.3-day decrease with each month over time. Four latent trajectories were identified in our cohort, with over 77% of individual trusts showing ongoing improvements in decreasing treatment waiting times. Prior to separating by latent class, time to DMARD initiation was shorter in trusts with higher rheumatology staffing, a local EIA treatment pathway and those with access to musculoskeletal ultrasound. Trusts with more nurses in the rheumatology department were less likely to be in the worse performance group (OR = 0.69 [95%CI 0.49, 0.93]). Conclusion In this cohort study, we observed a reduction in treatment waiting time over time. Trusts with better staffed and improved EIA clinical structure are likely to initiate definitive treatment earlier in patients with EIA. Disclosure Z. Yang: None. N. Arumalla: None. M.D. Russell: Honoraria; Lilly, Menarini, Galapagos. Grants/research support; NIHR. Other; Pfizer, Janssen, Biogen, and UCB. K. Bechman: Honoraria; Menarini, Galapagos. Grants/research support; NIHR,Versus Arthritis and Pfizer Global Medical Grants for Quality Improvement in Rheumatology Practice. Other; UCB. E. Alveyn: Other; UCB. S. Gallagher: None. E. Price: None. S. Norton: None. J. Galloway: Honoraria; AbbVie, Biovitrum, BMS, Celgene, Chugai, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Roche, Sanofi, Sobi and UCB.

Trajectory patterns and cumulative burden of CEA during follow-up with non-small cell lung cancer outcomes: A retrospective longitudinal cohort study.

Previous studies of non-small cell lung cancer (NSCLC) focused on CEA measured at a single time point, ignoring serial CEA measurements. This retrospective cohort included 2959 patients underwent surgery for stage I-III NSCLC. CEA trajectory patterns and long-term cumulative CEA burden were evaluated using the latent class growth mixture model. Four CEA trajectory groups were identified, named as low-stable, decreasing, early-rising and later-rising. Compared with the low-stable group, the adjusted hazard ratios associated with death were 1.27, 4.50, and 3.68 for the other groups. Cumulative CEA burden were positively associated with the risk of death in patients not belonging to the low-stable group. The 5-year overall survival (OS) rates decreased from 62.3% to 33.0% for the first and fourth quantile groups of cumulative CEA burden. Jointly, patients with decreasing CEA trajectory could be further divided into the decreasing & low and decreasing & high group, with 5-year OS rates to be 77.9% and 47.1%. Patients with rising CEA trajectory and high cumulative CEA were found to be more likely to develop bone metastasis. Longitudinal trajectory patterns and long-term cumulative burden of CEA were independent prognostic factors of NSCLC. We recommend CEA in postoperative surveillance of NSCLC.

Association of healthy lifestyle with life expectancy free of five major disabilities in Chinese older adults.

Whether and to what extent multiple healthy lifestyles affect the longevity of people with disabilities, including those in basic activities of daily living, mobility, vision, hearing and cognition, is crucial to policymakers. We aimed to determine the impact of combined lifestyles on life expectancy (LE) lived with and without five disabilities. We recruited participants (n = 15 121 from the China Longitudinal Healthy Longevity Survey between 2008 and 2018. Healthy lifestyle levels were estimated from six factors: smoking, drinking, physical exercise, diet, cognitive activity, and sleep, which we categorised as favourable and unfavourable using the latent class growth mixture model throughout the follow-up period. We used Multi-state Markov models to assess the different disability stages of LE. Of the total LE at age 65, older adults with a favourable lifestyle spent 59.60% (disability-free LE (DFLE) = 10.24 years) without five disabilities in combination, whereas those with unfavourable lifestyle spent 56.74% (DFLE = 7.28 years). Furthermore, the percentage of DFLE was 64.98 (7.71 years) and 68.38 (9.91 years) in males with unfavourable and favourable lifestyle levels, respectively, and 47.92 (6.62 years) and 55.12 (10.30 years) for females. Compared to older adults with low socioeconomic status (SES) and unfavourable lifestyle level, those with lower SES and favourable lifestyle level had more 3.77 years of DFLE, those with higher SES and unfavourable lifestyle level had more 1.94 years, as well as those with higher SES and favourable lifestyle level had more 5.10 years at age 65. Corresponding associations were found separately for each of the five individual disabilities. A favourable lifestyle level was associated with longer total LE along with a higher proportion of DFLE and may contribute to narrowing socioeconomic health inequalities. Policymakers should develop lifestyle interventions and scale up rehabilitation services in primary care, thereby delaying disabilities to later ages, especially in low- and middle-income countries.

Trajectories of Treatment Burden Among Primary Care Patients with Long-Term Conditions in Southern China: A Latent Class Growth Analysis.

Treatment burden is a patient-centred, dynamic concept. However, longitudinal data on the changing pattern of treatment burden among patients with one or more long-term conditions (LTCs) are relatively scanty. We aimed to explore the longitudinal trajectories of treatment burden and associated risk factors in a large, patient population in primary care settings. We analysed data from 5573 primary care patients with long-term conditions (LTCs) recruited using a multistage sampling method in Shenzhen, southern China. The treatment burden was assessed by the Mandarin Chinese version of the Treatment Burden Questionnaire (TBQ). We used latent class growth mixture modelling (LCGMM) to determine trajectories of treatment burden across four time points, ie, at baseline, and at 6, 12, and 18 months. Predictors of trajectory classes were explored using multivariable logistic regression analysis. The mean TBQ scores of patients with a single LTC (n = 2756), 2 LTCs (n = 1871), 3 LTCs (n = 699), and ≥4 LTCs (n = 247) were 18.17, 20.28, 21.32, and 26.10, respectively, at baseline. LCGMM identified three discrete classes of treatment burden trajectories over time, ie, a high-increasing class, a low-stable class, and a high-decreasing class. When controlling for individual-level factors including age, education, monthly household income per head, smoking, alcohol consumption, and attendance in health education, patients who had a clinical diagnosis of 3 LTCs (adjusted odds ratio [aOR] = 1.49, 95% CI = 1.21-1.86, P < 0.001) or ≥4 LTCs (aOR = 1.97, 95% CI = 1.44-2.72, P < 0.001) were more likely to belong to the high-increasing class. Sensitivity analysis using propensity score methods obtained similar results. Our study revealed the presence of discrete patterns of treatment burden over time in Chinese primary care patients with LTCs, providing directions for tailored interventions to optimise disease management. Patients with 3 or more LTCs should receive close attention in healthcare delivery as they tend to experience a greater treatment burden.

Trust performance in managing inflammatory arthritis over time in England and Wales: a latent class analysis approach.

To evaluate trust-level performance in time to initiation of DMARD therapy in patients with early inflammatory arthritis (EIA), with identification of the change in performance trajectories over time and investigation of trust characteristics associated with this change. We included 130 trusts from the UK contributing to the National Early Inflammatory Arthritis Audit (NEIAA) from 2018 to 2020. The primary outcome was days from referral to initiation of DMARD therapy in patients with EIA. Latent class growth mixture models were applied to identify distinct groups of trusts with similar trajectories of performance change over time. We used mixed effects linear and multinomial logistic regression models to evaluate the association between delay in treatment and trust-level characteristics. The mean time to DMARD initiation was 53days (s.d. 18), with an average 0.3-day decrease with each month over time. Four latent trajectories were identified in our cohort, with >77% of individual trusts showing ongoing improvements in decreasing treatment waiting times. Prior to separating by latent class, time to DMARD initiation was shorter in trusts with higher rheumatology staffing, a local EIA treatment pathway and those with access to musculoskeletal ultrasound. Trusts with more nurses in the rheumatology department were less likely to be in the worst performance group [odds ratio 0.69 (95% CI 0.49, 0.93)]. In this cohort study, we observed a reduction in treatment waiting time over time. Trusts with better staffed and improved EIA clinical structure are likely to initiate definitive treatment earlier in patients with EIA.

Anxiety trajectories from pregnancy to one-year postpartum and their contributors during the COVID-19 pandemic

ABSTRACT Background Anxiety in the peripartum period (pregnancy through one-year postpartum) has negative impacts on mothers and infants. During the COVID-19 pandemic, high rates of anxiety were reported worldwide, but trajectories for how these symptoms change longitudinally in the peripartum period remain unknown. Methods A total of 1,411 women who were pregnant during the second U.S. COVID-19 surge completed four study questionnaires between December 2020 and March 2022, including assessments of anxiety symptoms (GAD-7) and individual and community-level contributors. Latent Class Growth Mixture Models (LCGMM) were used to identify anxiety trajectories, and multinomial logistic regression was used to identify contributors to class membership. Results Three classes of anxiety symptom trajectories were identified. Class 1 (n = 956, 67.8%) experienced minimal/mild anxiety throughout the peripartum period. Class 2 (n = 362, 25.7%) experienced initial moderate anxiety that remained stable. Class 3 (n = 93, 6.6%) experienced initial moderate anxiety that increased to severe in the postpartum period. Stress and history of mental health diagnosis contributed to higher initial levels of anxiety and ongoing social support contributed to lower levels of anxiety. In addition, financial insecurity increased the risk of belonging to Class 3. Conclusions Screening for anxiety symptoms and psychosocial vulnerabilities in the peripartum period is vital, as is early intervention. This is especially the case among women with limited financial and social resources who may experience chronic or worsening anxiety as they transition to parenthood.

Trajectories of Blood Lipids Profile in Midlife Women: Does Menopause Matter?

It remains controversial whether changes of lipids over menopause transition (MT) are more age-related or more menopause-related. We aimed to classify women into different trajectory groups based on pattern and level of total cholesterol, low-density lipoprotein cholesterol, apolipoprotein B (ApoB), high-density lipoprotein cholesterol (HDL-C), triglyceride, and apolipoprotein A-I over the MT, as well as examine the effect of MT-related factors on lipid trajectory groups and levels. The cohort included 2582 subjects from the Study of Women's Health Across the Nation. Different trajectory patterns of lipids during the MT were determined using the latent class growth mixture model. The predictors of distinct blood lipids trajectory groups were determined by multiple linear regression models and multinomial logistic regression models. Women were categorized into either inverse U-shape or progressing trajectory group in each blood lipids measurement. The inverse U-shape total cholesterol, low-density lipoprotein cholesterol, apolipoprotein B, high-density lipoprotein cholesterol, log(TG), and apolipoprotein A-I trajectories showed an increasing trend before menopause but a decreasing trend after menopause. The U-shape total cholesterol, low-density lipoprotein cholesterol, and apolipoprotein B trajectories started to rise 5 years before menopause. Age at menopause, follicle-stimulating hormone, vasomotor symptoms, and estradiol predicted the shape and level of the women's lipids over the MT. Distinct lipid trajectories were identified during the MT, and the existence of at least 1 trajectory in each lipid parameters suggested a contribution of menopause. Our study highlights the need for earlier and continuous surveillance of lipids during the MT.

Remnant Cholesterol in Young Adulthood Is Associated With Left Ventricular Remodeling and Dysfunction in Middle Age: The CARDIA Study.

Recent studies have shown that remnant cholesterol (RC) is associated with incident heart failure; however, its association with left ventricular (LV) structure and function is unclear. We aimed to evaluate the association between RC levels in young adulthood and LV structure and function in middle age. We included 3321 participants from the CARDIA study (Coronary Artery Risk Development in Young Adults) at baseline. RC was calculated as total cholesterol minus high-density lipoprotein cholesterol minus calculated low-density lipoprotein cholesterol, and the RC trajectories that followed a similar pattern of change over time were identified using the latent class growth mixture model. LV structure and function were assessed using echocardiography at CARDIA study year 25. Multivariable linear regression models were performed to assess the associations of both baseline and trajectories of RC levels with LV structure and function. Among 3321 participants, the mean age was 24.99±3.62 years: 1450 (43.90%) were male, and 1561 (47.00%) were Black. After multivariate adjustment, higher baseline RC (per SD in log-transformed) was associated with higher LV mass index (β=1.29; P=0.004), worse global longitudinal strain (β=0.19; P<0.001), worse global circumferential strain (β=0.16; P=0.014), lower septal e' (β=-0.26; P<0.001), lower lateral e' (β=-0.18; P=0.003), and higher E/e' (β=0.15; P=0.003). Three RC trajectories were identified during follow-up: low increasing (42.4%), moderate increasing (45.5%), and high increasing (12.1%). Similarly, compared with the low-increasing group, the high-increasing RC trajectory group was related to higher LV mass index, worse global longitudinal strain, lower septal e', lower lateral e', and higher E/e'. Elevated RC levels in young adulthood were related to adverse LV structural and functional alterations in midlife. Long-term trajectories of RC levels during young adulthood help identify individuals at a higher risk for adverse LV remodeling and dysfunction. URL: https://www.clinicaltrials.gov; Unique identifier: NCT00005130.

20-year trajectories of positive and negative symptoms after the first psychotic episode in patients with schizophrenia spectrum disorder: results from the OPUS study.

This study aimed to identify the 20-year trajectories of positive and negative symptoms after the first psychotic episode in a sample of patients with an ICD-10 diagnosis of schizophrenia spectrum disorder, and to investigate the baseline characteristics and long-term outcomes associated with these trajectories. A total of 373 participants in the OPUS trial were included in the study. Symptoms were assessed at baseline and after 1, 2, 5, 10 and 20 years using the Scales for the Assessment of Positive and Negative Symptoms. We used latent class growth mixture modelling to identify trajectories, and multinominal regression analyses to investigate predictors of membership to identified trajectories. Five trajectories of positive symptoms were identified: early continuous remission (50.9% of the sample), stable improvement (18.0%), intermittent symptoms (10.2%), relapse with moderate symptoms (11.9%), and continuous severe symptoms (9.1%). Substance use disorder (odds ratio, OR: 2.83, 95% CI: 1.09-7.38, p=0.033), longer duration of untreated psychosis (OR: 1.02, 95% CI: 1.00-1.03, p=0.007) and higher level of negative symptoms (OR: 1.60, 95% CI: 1.07-2.39, p=0.021) were predictors of the relapse with moderate symptoms trajectory, while only longer duration of untreated psychosis (OR: 1.01, 95% CI: 1.00-1.02, p=0.030) predicted membership to the continuous severe symptoms trajectory. Two trajectories of negative symptoms were identified: symptom remission (51.0%) and continuous symptoms (49.0%). Predictors of the continuous symptoms trajectory were male sex (OR: 3.03, 95% CI: 1.48-6.02, p=0.002) and longer duration of untreated psychosis (OR: 1.01, 95% CI: 1.00-1.02, p=0.034). Trajectories displaying continuous positive and negative symptoms were linked to lower neurocognition, as measured by the Brief Assessment of Cognition in Schizophrenia (BACS) (z-score: -0.78, CI: -1.39 to -0.17, for continuous positive symptoms; z-score: -0.33, CI: -0.53 to -0.13, for continuous negative symptoms). The same trajectories were also linked to higher use of antipsychotic medication at 20-year follow-up (continuous positive symptoms: 78%; continuous negative symptoms: 67%). These findings suggest that the majority of patients with first-episode schizophrenia spectrum disorder have a trajectory with early stable remission of positive symptoms. Long duration of untreated psychosis and comorbid substance abuse are modifiable predictors of poor trajectories for positive symptoms in these patients. In about half of patients, negative symptoms do not improve over time. These symptoms, in addition to being associated with poor social and neurocognitive functioning, may prevent patients from seeking help.

Association of blood pressure trajectories with coronary heart disease among the disabled population in Shanghai, China: a cohort study of 7 years following up

BackgroundMuch less is known about the importance of blood pressure (BP) trajectories concerning the incidence of coronary heart disease (CHD) in people with disabilities. Our aim was to evaluate this association.MethodsThis cohort study surveyed 5711 adults from the Shanghai Disability Health Survey from June 2012 to June 2019. The latent class growth mixture model was used to examine distinct BP trajectories. We evaluated the association of BP trajectories with the risk of CHD by Cox proportional hazard models. The model for CHD risk fitted to BP trajectories was compared with models fitted to other BP-related indicators by goodness-of-fit, discrimination, and calibration.ResultsDuring a median follow-up of 71.74 months, 686 cases (median age was 49.03 (54.49, 58.55) years, 51.90% female) with CHD were identified, with a cumulative incidence of 12.01%. Systolic BP (SBP) and diastolic BP (DBP) were categorized into three classes, respectively. A statistically significant association was only observed between SBP trajectories and CHD. Compared with the normotensive stable SBP group (n = 1956), the prehypertension-stable group (n = 3268) had a higher risk (adjust hazards ratio (aHR) = 1.266, 95% confidence interval (CI) 1.014–1.581), and the stage 1 hypertension-decreasing group (n = 487) had the highest risk (aHR = 1.609, 95%CI 1.157–2.238). Among the BP-related indicators, the SBP trajectory was the strongest predictor of new-onset CHD. Findings were similar when sensitivity analyses were conducted.ConclusionsSBP trajectory was a more important risk factor for CHD than other BP-related indicators and stringent BP control strategies may be effective for primary CHD prevention in the disabled population.

Trajectories of Traumatic Stress Symptoms Among Siblings of Children With Cancer: The First Two Years Post-Diagnosis.

Identify and describe trajectories of cancer-related posttraumatic stress symptoms (PTSS) among siblings of children with cancer within two years of diagnosis. Siblings (aged 8-18; M = 11.2 years) across the United States, and for each, one caregiver, were recruited for a cohort sequential longitudinal study with three data collection points six months apart beginning at 6- or 12-months after cancer diagnosis. Siblings (N = 229; 42% of eligible/approached; 53% identifying as female; 68% identifying as non-Hispanic White) completed the Child Posttraumatic Stress Disorder Symptom Scale. Caregivers completed the Strengths and Difficulties Questionnaire (SDQ). Latent class growth analysis (LCGA) and growth mixture modeling (GMM) identified PTSS patterns across time. Fit statistics supported models with three to five PTSS trajectories. The three-class LCGA model included a large mild PTSS group (61%), a moderate PTSS group (35%), and a small (4%) stable severe PTSS group. The four-class LCGA and three- and four-class GMM included groups improving from moderate to mild PTSS (7-21%) and worsening to moderate PTSS across time (12-17%). Across models, siblings with mild PTSS had fewer caregiver-reported emotional and behavioral difficulties on the SDQ. A large group of siblings of children with cancer demonstrate resiliency, however, substantial subsets experience patterns of PTSS that include levels in the moderate-to-severe range during the first two years post-diagnosis. Future research should examine these patterns in more diverse/representative samples and identify factors associated with increasing and sustained severe PTSS to inform intervention targets and reduce cancer-related burden on families.